Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Drug Nomenclature01:17

Drug Nomenclature

2.7K
During the development of a new pharmaceutical, the manufacturer initially assigns a code name to the drug. Once approved, the drug receives a United States Adopted Name (USAN)—a generic, nonproprietary designation. Upon being listed in the United States Pharmacopeia, this nonproprietary name becomes the drug's official name. Additionally, the manufacturer assigns a proprietary name or trademark, which serves as the brand name under which the drug is marketed. It is worth noting that...
2.7K
Opioid Analgesics: Synthetic and Semisynthetic Opioids01:15

Opioid Analgesics: Synthetic and Semisynthetic Opioids

679
Synthetic and semisynthetic opioids are pivotal in pain management and tackling opioid addiction. Semisynthetic opioids, including morphinans (morphine derivatives), oxycodone, oxymorphone, hydrocodone, and hydromorphone, have improved pharmacokinetic profiles compared to morphine. Additionally, heroin and 6-MAM (6-Monoacetylmorphine) show better CNS penetration than morphine due to heightened lipid solubility. Hydromorphone, a potent opioid, undergoes hepatic metabolism to form the active...
679
Methods of Documentation VII: EMR01:30

Methods of Documentation VII: EMR

1.2K
Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare...
1.2K
Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

6.0K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
6.0K
Opioid Analgesics: Morphine and Other Natural Cogeners01:20

Opioid Analgesics: Morphine and Other Natural Cogeners

605
Opioids are a class of drugs that mimic endogenous opioid peptides and act on opioid receptors, and help in pain relief. These compounds are classified as natural, synthetic, or semi-synthetic. Natural opioids, like morphine, codeine, and thebaine, are derived from the opium poppy plant (Papaver somniferum or Papaver album) and are termed opiates. Synthetic opioids are artificial, while semi-synthetic opioids combine natural and synthetic compounds. Morphine, a prototypical opioid, possesses a...
605
Drug Dependence01:17

Drug Dependence

1.4K
Medications are typically administered to achieve therapeutic effects. Some drugs can modify an individual's mood and perception, frequently resulting in various enjoyable experiences. However, this can result in drug dependency, a condition marked by continuous drug use despite potential negative consequences. Drug dependency primarily falls into two categories: psychological and physical dependence. Psychological dependence occurs when the pleasurable feelings induced by the drug...
1.4K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Patient out-of-pocket costs for antihypertensive single pill combination products with cost caps.

Journal of human hypertension·2026
Same author

A Qualitative Assessment of an Electronic Health Record-Embedded Intervention to Increase In-Hospital Opioid Use Disorder Treatment Initiation.

Journal of general internal medicine·2026
Same author

Automated Health Care Messages and Unexpected Patient Responses.

JAMA network open·2026
Same author

Fifty Years From the First Framingham Risk Profile: Are We Getting Closer to Identifying and PREVENTing Subclinical Disease Progression?

Journal of the American Heart Association·2026
Same author

Hepatitis B Vaccine Series Completion by 18 Months in Infants Without a Birth Dose.

JAMA network open·2026
Same author

Burden of all-cause and cause-specific mortality among individuals with medications for treatment of opioid use disorder: A matched cohort study from 4 US health systems, 2012-2021.

Journal of substance use and addiction treatment·2026

Related Experiment Video

Updated: Nov 25, 2025

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

16.2K

Identifying naloxone administrations in electronic health record data using a text-mining tool.

Catherine G Derington1, Shane R Mueller2, Jason M Glanz2,3

  • 1Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA.

Substance Abuse
|December 15, 2020
PubMed
Summary

A new text-mining tool significantly improves identifying naloxone administrations in electronic health records (EHR), boosting accuracy from under 60% to over 80% for overdose surveillance and research.

Keywords:
Naloxoneclinical noteselectronic health recordpositive predictive valuetext mining

More Related Videos

Author Spotlight: An Efficient Methodology to Confidently Differentiate and Characterize Fentanyl Analogs
10:13

Author Spotlight: An Efficient Methodology to Confidently Differentiate and Characterize Fentanyl Analogs

Published on: November 8, 2024

2.6K
Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
05:10

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

10.0K

Related Experiment Videos

Last Updated: Nov 25, 2025

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

16.2K
Author Spotlight: An Efficient Methodology to Confidently Differentiate and Characterize Fentanyl Analogs
10:13

Author Spotlight: An Efficient Methodology to Confidently Differentiate and Characterize Fentanyl Analogs

Published on: November 8, 2024

2.6K
Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
05:10

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

10.0K

Area of Science:

  • Health Informatics
  • Natural Language Processing
  • Public Health Surveillance

Background:

  • Accurate identification of naloxone administrations in electronic health records (EHR) is crucial for effective overdose surveillance and research.
  • Existing methods, such as administrative code queries, have limitations in accurately capturing naloxone administration events within EHR data.

Purpose of the Study:

  • To develop and validate a text-mining tool for accurately identifying naloxone administrations within clinical notes in EHR data.
  • To compare the performance of the developed text-mining tool against traditional administrative code queries for naloxone identification.

Main Methods:

  • Iterative development of a text-mining tool using clinical notes from January 2017 to March 2018.
  • Initial broad search terms were refined through review of overdose encounters and identification of specific naloxone administration phrases.
  • Validation involved comparing the tool's output against medical record reviews and an administrative code query.

Main Results:

  • The final iteration of the text-mining tool achieved a positive predictive value (PPV) of 83.8% (95% CI 78.6-88.2%).
  • The second iteration of the tool demonstrated a PPV of 84.3% (95% CI 78.6-89.0%).
  • The administrative code query had a significantly lower PPV of 57.1% (95% CI 47.1-66.8%), with both text-mining iterations outperforming it (p < 0.001).

Conclusions:

  • The developed text-mining tool substantially enhances the accuracy of identifying naloxone administrations in EHR data, exceeding 80% PPV.
  • Text-mining offers a more effective approach compared to administrative codes for naloxone administration surveillance in EHRs.
  • This informatics method provides a foundation for more sophisticated analyses, despite potential resource and expertise requirements.